Stochastic optimization of multireservoir systems via reinforcement learning

Although several variants of stochastic dynamic programming have been applied to optimal operation of multireservoir systems, they have been plagued by a high‐dimensional state space and the inability to accurately incorporate the stochastic environment as characterized by temporally and spatially c...

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Bibliographic Details
Published in:	Water resources research Vol. 43; no. 11
Main Authors:	Lee, J.H, Labadie, J.W
Format:	Journal Article
Language:	English
Published:	Blackwell Publishing Ltd 01.11.2007
Subjects:	case studies dynamic models dynamic programming Geum hydrologic models mathematical models Monte Carlo method optimization probabilistic models reinforcement learning reservoirs rivers spatial variation stochastic optimization stochastic processes temporal variation water flow South Korea Korea, Rep
ISSN:	0043-1397, 1944-7973
Online Access:	Get full text
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